Rainfall variability, fire and vegetation dynamics in neotropical montane ecosystems in north-western Argentina

2000 ◽  
Vol 27 (5) ◽  
pp. 1107-1121 ◽  
Author(s):  
Hector Ricardo Grau ◽  
Thomas T. Veblen
Keyword(s):  
Vegetation Dynamics ◽  
Rainfall Variability ◽  
North Western

scholarly journals Rainfall variability from a dense rain gauge network in north-western Italy

2018 ◽  
Vol 75 (3) ◽  
pp. 201-213 ◽  
Author(s):  
A Baronetti ◽  
F Acquaotta ◽  
S Fratianni
Keyword(s):  
Rainfall Variability ◽  
Rain Gauge ◽  
Rain Gauge Network ◽  
North Western

scholarly journals RESPONSE OF RIPARIAN VEGETATION IN AUSTRALIA"S LARGEST RIVER BASIN TO INTER AND INTRA-ANNUAL CLIMATE VARIABILITY AND FLOODING AS QUANTIFIED WITH LANDSAT AND MODIS

2016 ◽  
Vol XLI-B8 ◽  
pp. 577-578
Author(s):  
M. Broich ◽  
M. G. Tulbure
Keyword(s):  
River Basin ◽  
Vegetation Dynamics ◽  
Riparian Vegetation ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Spatially Explicit ◽  
Rainfall Gradient ◽  
Vegetation Degradation ◽  
Millennium Drought ◽  
Okavango River

Australia is a continent subject to high rainfall variability, which has major influences on runoff and vegetation dynamics. However, the resulting spatial-temporal pattern of flooding and its influence on riparian vegetation has not been quantified in a spatially explicit way. Here we focused on the floodplains of the entire Murray-Darling Basin (MDB), an area that covers over 1M km<sup>2</sup>, as a case study. The MDB is the country’s primary agricultural area with scarce water resources subject to competing demands and impacted by climate change and more recently by the Millennium Drought (1999–2009). Riparian vegetation in the MDB floodplain suffered extensive decline providing a dramatic degradation of riparian vegetation. <br><br> We quantified the spatial-temporal impact of rainfall, temperature and flooding patters on vegetation dynamics at the subcontinental to local scales and across inter to intra-annual time scales based on three decades of Landsat (25k images), Bureau of Meteorology data and one decade of MODIS data. <br><br> Vegetation response varied in space and time and with vegetation types, densities and location relative to areas frequently flooded. Vegetation degradation trends were observed over riparian forests and woodlands in areas where flooding regimes have changed to less frequent and smaller inundation extents. Conversely, herbaceous vegetation phenology followed primarily a ‘boom’ and ‘bust’ cycle, related to inter-annual rainfall variability. Spatial patters of vegetation degradation changed along the N-S rainfall gradient but flooding regimes and vegetation degradation patterns also varied at finer scale, highlighting the importance of a spatially explicit, internally consistent analysis and setting the stage for investigating further cross-scale relationships. <br><br> Results are of interest for land and water management decisions. The approach developed here can be applied to other areas globally such as the Nile river basin and Okavango River delta in Africa or the Mekong River Basin in Southeast Asia.

scholarly journals RESPONSE OF RIPARIAN VEGETATION IN AUSTRALIA"S LARGEST RIVER BASIN TO INTER AND INTRA-ANNUAL CLIMATE VARIABILITY AND FLOODING AS QUANTIFIED WITH LANDSAT AND MODIS

2016 ◽  
Vol XLI-B8 ◽  
pp. 577-578
Author(s):  
M. Broich ◽  
M. G. Tulbure
Keyword(s):  
River Basin ◽  
Vegetation Dynamics ◽  
Riparian Vegetation ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Spatially Explicit ◽  
Rainfall Gradient ◽  
Vegetation Degradation ◽  
Millennium Drought ◽  
Okavango River

Australia is a continent subject to high rainfall variability, which has major influences on runoff and vegetation dynamics. However, the resulting spatial-temporal pattern of flooding and its influence on riparian vegetation has not been quantified in a spatially explicit way. Here we focused on the floodplains of the entire Murray-Darling Basin (MDB), an area that covers over 1M&thinsp;km<sup>2</sup>, as a case study. The MDB is the country’s primary agricultural area with scarce water resources subject to competing demands and impacted by climate change and more recently by the Millennium Drought (1999&ndash;2009). Riparian vegetation in the MDB floodplain suffered extensive decline providing a dramatic degradation of riparian vegetation. <br><br> We quantified the spatial-temporal impact of rainfall, temperature and flooding patters on vegetation dynamics at the subcontinental to local scales and across inter to intra-annual time scales based on three decades of Landsat (25k images), Bureau of Meteorology data and one decade of MODIS data. <br><br> Vegetation response varied in space and time and with vegetation types, densities and location relative to areas frequently flooded. Vegetation degradation trends were observed over riparian forests and woodlands in areas where flooding regimes have changed to less frequent and smaller inundation extents. Conversely, herbaceous vegetation phenology followed primarily a ‘boom’ and ‘bust’ cycle, related to inter-annual rainfall variability. Spatial patters of vegetation degradation changed along the N-S rainfall gradient but flooding regimes and vegetation degradation patterns also varied at finer scale, highlighting the importance of a spatially explicit, internally consistent analysis and setting the stage for investigating further cross-scale relationships. <br><br> Results are of interest for land and water management decisions. The approach developed here can be applied to other areas globally such as the Nile river basin and Okavango River delta in Africa or the Mekong River Basin in Southeast Asia.

scholarly journals Effects of Climate Variability on Normalized Difference Vegetation Index (NDVI) in the Gojeb River Catchment, Omo-Gibe Basin, Ethiopia

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Melku Dagnachew ◽  
Asfaw Kebede ◽  
Awdenegest Moges ◽  
Adane Abebe
Keyword(s):  
Climate Variability ◽  
Trend Analysis ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rainfall Variability ◽  
Time Lag ◽  
Rainfall Time Series ◽  
River Catchment ◽  
Vegetation Degradation

Vegetation dynamics have been visibly influenced by climate variability. The Normalized Difference Vegetation Index (NDVI) has been the most commonly used index in vegetation dynamics. The study was conducted to examine the effects of climatic variability (rainfall) on NDVI for the periods 1982–2015 in the Gojeb River Catchment (GRC), Omo-Gibe Basin, Ethiopia. The spatiotemporal trend in NDVI and rainfall time series was assessed using a Theil–Sen (Sen) slope and Mann–Kendall (MK) statistical significance test at a 95% confidence interval. Moreover, the residual trend analysis (RESTREND) method was used to investigate the effect of rainfall and human induction on vegetation degradation. The Sen’s slope trend analysis and MK significant test indicated that the magnitude of annual NDVI and rainfall showed significant decrement and/or increment in various portions of the GRC. The concurrent decrement and/or increment of annual NDVI and rainfall distributions both spatially and temporarily could be attributed to the significant positive correlation of the monthly (RNDVI-RF = 0.189, P≤0.001) and annual (RNDVI-RF = 0.637, P≤0.001) NDVI with rainfall in almost all portions of the catchment. In the GRC, a strongly negative decrement and strong positive increment of NDVI could be derived by human-induced and rainfall variability, respectively. Accordingly, the significant NDVI decrement in the downstream portion and significant increment in the northern portion of the catchment could be attributed to human-induced vegetation degradation and the variability of rainfall, respectively. The dominance of a decreasing trend in the residuals at the pixel level for the NDVI from 1982, 1984, 2000, 2008 to 2012 indicates vegetation degradation. The strong upward trend in the residuals evident from 1983, 1991, 1998 to 2007 was indicative of vegetation improvements. In the GRC, the residuals may be derived from climatic variations (mainly rainfall) and human activities. The time lag between NDVI and climate factors (rainfall) varied mainly from two to three months. In the study catchment, since vegetation degradations are mainly caused by human induction and rainfall variability, integrated and sustainable landscape management and climate-smart agricultural practices could have paramount importance in reversing the degradation processes.

scholarly journals Rainfall variability and vegetation dynamics in the Mauritanian Sahel

2008 ◽  
Vol 38 ◽  
pp. 75-81 ◽  
Author(s):  
OCA Ahmedou ◽  
R Nagasawa ◽  
AE Osman ◽  
K Hattori
Keyword(s):  
Vegetation Dynamics ◽  
Rainfall Variability

scholarly journals Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data

2011 ◽  
Vol 8 (11) ◽  
pp. 3359-3373 ◽  
Author(s):  
C. Höpfner ◽  
D. Scherer
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Vegetation Dynamics ◽  
Time Series Data ◽  
Series Data ◽  
Land Cover Types ◽  
Modis Ndvi ◽  
Ndvi Time Series ◽  
Western Morocco ◽  
North Western

Abstract. Vegetation phenology as well as the current variability and dynamics of vegetation and land cover, including its climatic and human drivers, are examined in a region in north-western Morocco that is nearly 22 700 km2 big. A gapless time series of Normalized Differenced Vegetation Index (NDVI) composite raster data from 29 September 2000 to 29 September 2009 is utilised. The data have a spatial resolution of 250 m and were acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The presented approach allows to compose and to analyse yearly land cover maps in a widely unknown region with scarce validated ground truth data by deriving phenological parameters. Results show that the high temporal resolution of 16 d is sufficient for (a) determining local land cover better than global land cover classifications of Plant Functional Types (PFT) and Global Land Cover 2000 (GLC2000) and (b) for drawing conclusions on vegetation dynamics and its drivers. Areas of stably classified land cover types (i.e. areas that did not change their land cover type) show climatically driven inter- and intra-annual variability with indicated influence of droughts. The presented approach to determine human-driven influence on vegetation dynamics caused by agriculture results in a more than ten times larger area compared with stably classified areas. Change detection based on yearly land cover maps shows a gain of high-productive vegetation (cropland) of about 259.3 km2. Statistically significant inter-annual trends in vegetation dynamics during the last decade could however not be discovered. A sequence of correlations was respectively carried out to extract the most important periods of rainfall responsible for the production of green biomass and for the extent of land cover types. Results show that mean daily precipitation from 1 October to 15 December has high correlation results (max. r2=0.85) on an intra-annual time scale to NDVI percentiles (50 %) of land cover types. Correlation results of mean daily precipitation from 16 September to 15 January and percentage of yearly classified area of each land cover type are medium up to high (max. r2=0.64). In all, an offset of nearly 1.5 months is detected between precipitation rates and NDVI values. High-productive vegetation (cropland) is proved to be mainly rain-fed. We conclude that identification, understanding and knowledge about vegetation phenology, and current variability of vegetation and land cover, as well as prediction methods of land cover change, can be improved using multi-year MODIS NDVI time series data. This study enhances the comprehension of current land surface dynamics and variability of vegetation and land cover in north-western Morocco. It especially offers a quick access when estimating the extent of agricultural lands.

scholarly journals Recent Rainfall Variability Over a Dryland Ecosystem of North Western India

2021 ◽  
Author(s):  
DIVYA SAINI ◽  
PANKAJ BHARDWAJ ◽  
Omvir Singh
Keyword(s):  
Rainfall Variability ◽  
Climatic Conditions ◽  
Annual Rainfall ◽  
Western India ◽  
Positive Trend ◽  
North West ◽  
North East ◽  
Mean Annual Rainfall ◽  
The Mean ◽  
North Western

Abstract In this study, an attempt has been made to examine the recent rainfall variability by means of daily rainfall data of 33 well spread stations over dryland ecosystem of Rajasthan in north western India during 1961-2017. For trend analysis, Mann-Kendall, Sen’s slope estimator and simple linear regression test have been used (at 95% confidence level). The results have shown a high interannual variability in rainfall occurrence varying from 277 mm (in year 2002) to 839 mm (in year 1975) with mean of 583 mm over this dryland ecosystem. Most of the rainfall deficit years have occurred with El-Nino years. The mean annual rainfall has shown a marginal non-significant upward trend over the ecosystem. The station-wise mean annual rainfall has revealed a significant rising trend over Barmer, Churu, Ganganagar, Jaisalmer and Pratapgarh stations. Interestingly, three year running average has shown a cyclic pattern of rainfall over dryland ecosystem under the changing climatic conditions. The spatial pattern has exhibited that the mean annual rainfall decreases from east and south east (more than 850 mm) to west and north west (less than 400 mm), which is mainly associated with the presence of Aravalli Mountains spreading north east to south west in central Rajasthan. Remarkably, majority of stations positioned in western parts of dryland ecosystem have shown increasing rainfall trends, whereas some stations located in eastern parts have recorded a non-significant declining trend. The magnitude of significant rising trend has varied from 5.34 mm/year (Pratapgarh station) to 2.17 mm/year (Jaisalmer station). Also, the frequency of heavy rainfall events has shown a positive trend with significant increasing trends over Bharatpur, Jaisalmer and Pratapgarh stations, whereas Bundi station has shown significant decreasing trend.

scholarly journals Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data

2011 ◽  
Vol 8 (2) ◽  
pp. 3953-3998 ◽  
Author(s):  
C. Höpfner ◽  
D. Scherer
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Vegetation Dynamics ◽  
Time Series Data ◽  
Series Data ◽  
Land Cover Types ◽  
Modis Ndvi ◽  
Ndvi Time Series ◽  
Western Morocco ◽  
North Western

Abstract. Vegetation phenology as well as current variability and dynamics of vegetation and land cover including its climatic and human drivers are examined in a region in north-western Morocco of nearly 22 700 km2. A gapless time series of Normalized Differenced Vegetation Index (NDVI) composite raster data from 29 September 2000 to 29 September 2009 with a spatial resolution of 250 m and acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is utilised. The presented approach allows to compose and analyse yearly land cover maps in a widely unknown region with scarce validated ground truth data by deriving phenological parameters. Results show that high temporal resolution of 16 d is sufficient (a) for determining land cover better than global land cover classifications of Plant Functional Types (PFT) and Global Land Cover 2000 (GLC2000), and (b) for drawing conclusions on vegetation dynamics and its drivers. Areas of stably classified land cover types show climatically driven inter- and intra-annual variability with indicated influence of droughts. The presented approach to determine human-driven influence on vegetation dynamics caused by agriculture results in a more than ten times larger area compared to the stably classified areas. Change detection based on yearly land cover maps shows a gain of high-productive vegetation (cropland) of about 259.3 km2. However, statistically significant inter-annual trends in vegetation dynamics during the last decade could not be discovered. A sequence of correlations was done to extract the most important period of rainfall for production of green biomass and for the extent of land cover types, respectively. Results show that mean daily precipitation from 1 October to 15 December has high correlation results (max. r2=0.85) at intra-annual time scale to NDVI percentiles (50%) of land cover types. Correlation results of mean daily precipitation from 16 September to 15 January and percentage of yearly classified area of each land cover type are medium up to high (max. r2=0.64). In all, an offset of nearly 1.5 months is detected between precipitation rates and NDVI in 16 d steps. High-productive vegetation (cropland) is proved to be mainly rain-fed. We conclude that identification, understanding and knowledge about vegetation phenology, and current variability of vegetation and land cover as well as prediction methods of land cover change can be improved using multi-year MODIS NDVI time series data. This study enhances the comprehension of current land surface dynamics and variability of vegetation and land cover in north-western Morocco offering a fast access especially for estimating the extent of agricultural lands.

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